Energy-saving information calculation method, device, equipment, medium and product of data machine room

Abstract

The invention provides an energy-saving information calculation method and device for a data machine room, equipment, a medium and a product, and the method comprises the steps: collecting a use record of the data machine room, the use record comprising electric quantity use information and / or temperature information of an original mode day, and daily electric quantity use information and / or temperature information of a plurality of energy-saving mode days; using the use record to generate a time sequence of a specified dimension; performing similarity calculation on the time sequence data by adopting a DTW algorithm to generate a similarity matrix; according to the similarity matrix, determining one energy-saving mode day with the highest similarity with one original mode day as an energy-saving mode comparison day; and performing energy-saving information calculation according to the electricity consumption of the original mode day and the electricity consumption of the energy-saving mode comparison day. According to the embodiment of the invention, the reliability of measurement and verification of the energy-saving information can be improved, the energy-saving evaluation effect is improved, and the energy utilization efficiency of the communication machine room can be further improved.

Description

Background Art

[0002] At present, in the field of data centers, energy saving of refrigeration systems is an important component. Energy saving of refrigeration systems generally refers to reducing the power consumption of refrigeration systems by optimizing air conditioning control and airflow organization, thereby reducing the PUE of data centers and achieving green energy saving. In data center green energy saving and old computer room renovation projects, energy saving is the most important evaluation indicator.

[0003] In the relevant technology, the "direct comparison method" is mainly used to calculate the energy saving of the computer room. The "direct comparison method" refers to selecting two or more measurement days as similar days under the normal working conditions of the communication room, and measuring and verifying the energy saving amount by comparing the changes in the energy consumption of the computer room when the energy-saving measures are turned on and off.

[0004] However, the “direct comparison method” has at least the following technical defects:

[0005] 1. The daily granularity of parameter selection is too coarse, resulting in low accuracy of calculated energy saving information.

[0006] 2. Only the average daily temperature was selected as a parameter, and the deviations of multiple parameters were not comprehensively considered.

[0007] 3. The calculation process of the "direct comparison method" does not correct the errors caused by IT load changes.

[0008] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0009] The purpose of the present disclosure is to provide a method, device, equipment, medium and product for calculating energy-saving information of a data center, which is used to overcome the problems of poor reliability of calculation results of energy-saving information caused by limitations and defects of related technologies at least to a certain extent.

[0010] According to a first aspect of an embodiment of the present disclosure, a method for calculating energy-saving information of a data room is provided, comprising: collecting usage records of the data room, the usage records comprising power usage information and / or temperature information of an original mode day, and power usage information and / or temperature information of each of multiple energy-saving mode days; generating a time series of a specified dimension from the usage records; performing similarity calculation on the time series data using a DTW algorithm to generate a similarity matrix; determining, according to the similarity matrix, an energy-saving mode day that has the highest similarity to the original mode day as an energy-saving mode comparison day; and calculating energy-saving information according to the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day.

[0011] In an exemplary embodiment of the present disclosure, collecting the usage records of the data center includes:

[0012] Collecting indoor temperature records and outdoor temperature records of the data room on a daily basis;

[0013] The indoor document record and the outdoor temperature record are determined as the temperature information.

[0014] In an exemplary embodiment of the present disclosure, collecting the usage records of the data center further includes:

[0015] Determining the type of electricity consumption records to be collected according to the type of the cabinet in the data room;

[0016] Collecting the electricity consumption records of the corresponding types of the first cabinets of each type in the data center in each specified time period on a daily basis, wherein the electricity consumption records include at least one of current, voltage value, power consumption and occupancy rate of the server;

[0017] The collected electricity usage records are normalized to obtain the electricity usage information.

[0018] In an exemplary embodiment of the present disclosure, generating a time series of a specified dimension from the usage record includes:

[0019] Splicing the usage records collected in days into a feature sequence, and normalizing the data of each dimension of the feature sequence;

[0020] Average the normalized feature sequences of any two energy-saving mode days;

[0021] The PCA algorithm is used to perform dimension reduction processing on the feature sequence after averaging processing to obtain the time series.

[0022] In an exemplary embodiment of the present disclosure, using the DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix includes:

[0023] Using the DTW algorithm to calculate the DTW distance between the time series of the original mode day and any of the energy-saving mode days;

[0024] The similarity matrix is ​​generated according to the calculation result of the DTW distance.

[0025] In an exemplary embodiment of the present disclosure, the energy-saving information calculation includes energy-saving rate calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day includes:

[0026] The energy saving rate calculation formula is used to calculate the energy saving rate of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving rate calculation formula includes:

[0027]

[0028] Among them, the η s Characterize the result of energy saving rate calculation, the S r represents the power consumption of the original mode day, the S b Indicates the daily power consumption of the energy-saving mode.

[0029] In an exemplary embodiment of the present disclosure, the energy-saving information calculation includes energy-saving amount calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day further includes:

[0030] The energy saving amount calculation formula is used to calculate the energy saving amount of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving amount calculation formula includes:

[0031]

[0032] Among them, the E s Characterize the result of energy saving calculation, the E b Represents the total power consumption of the original mode day and all the energy-saving mode days.

[0033] According to a second aspect of an embodiment of the present disclosure, there is provided an energy-saving information calculation device for a data center, comprising:

[0034] A collection module configured to collect usage records of a data room, wherein the usage records include power usage information and / or temperature information of an original mode day, and daily power usage information and / or temperature information of multiple energy-saving mode days;

[0035] A generating module, configured to generate a time series of a specified dimension from the usage record;

[0036] A comparison module is configured to use a DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix;

[0037] A determination module, configured to determine, according to the similarity matrix, an energy-saving mode day having the highest similarity to an original mode day as an energy-saving mode comparison day;

[0038] The calculation module is configured to calculate energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day.

[0039] According to a third aspect of the present disclosure, there is provided an electronic device, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute any one of the methods described above based on instructions stored in the memory.

[0040] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a program is stored, and when the program is executed by a processor, the method for calculating energy-saving information of a data center as described in any one of the above items is implemented.

[0041] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, characterized in that when the computer program is executed by a processor, the method for calculating energy-saving information of a data center as described in any one of the above is implemented.

[0042] The disclosed embodiment collects usage records of a data room, wherein the usage records include power usage information and / or temperature information of an original mode day and power usage information and / or temperature information of each of multiple energy-saving mode days, and generates a time series of a specified dimension from the usage records, and then uses a DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix, and then determines, based on the similarity matrix, an energy-saving mode day that has the highest similarity to the original mode day as an energy-saving mode comparison day, and finally calculates energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day, thereby improving the reliability of measurement and verification of energy-saving information, improving the evaluation of energy-saving effects, and facilitating further improving the energy efficiency of the communication room.

[0043] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0045] Figure 1 A schematic diagram showing an exemplary system architecture of a data center energy-saving information calculation solution to which an embodiment of the present invention can be applied;

[0046] Figure 2 is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure;

[0047] Figure 3is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure;

[0048] Figure 4 is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure;

[0049] Figure 5 is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure;

[0050] Figure 6 is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure;

[0051] Figure 7 is a schematic diagram of a DTW algorithm of an energy-saving information calculation solution for a data center in an exemplary embodiment of the present disclosure;

[0052] Figure 8 is a flow chart of a data center energy saving information calculation scheme in an exemplary embodiment of the present disclosure;

[0053] Fig. 9 is a block diagram of an energy-saving information calculation device for a data center in an exemplary embodiment of the present disclosure;

[0054] Fig.10 is a block diagram of an electronic device in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0055] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as being limited to the examples set forth herein; on the contrary, these embodiments are provided so that the present disclosure will be more comprehensive and complete, and the concepts of the example embodiments are fully conveyed to those skilled in the art. The described features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known technical solutions are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0056] In addition, the accompanying drawings are only schematic diagrams of the present disclosure, and the same reference numerals in the drawings represent the same or similar parts, so their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0057] Figure 1 A schematic diagram showing an exemplary system architecture of a data center energy-saving information calculation solution to which an embodiment of the present invention can be applied is shown.

[0058] like Figure 1 As shown, the system architecture 100 may include one or more of terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0059] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 105 may be a server cluster composed of multiple servers.

[0060] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Terminal devices 101, 102, 103 can be various electronic devices with display screens, including but not limited to smart phones, tablet computers, portable computers, desktop computers, etc.

[0061] In some embodiments, the energy-saving information calculation method for a data center provided by the embodiments of the present invention is generally executed by the server 105. Accordingly, the energy-saving information calculation device for a data center is generally arranged in the terminal device 103 (or the terminal device 101 or 102). In other embodiments, some terminals may have functions similar to those of the server device to execute the method.

[0062] The exemplary embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0063] Figure 2 It is a flow chart of a method for calculating energy-saving information of a data center in an exemplary embodiment of the present disclosure.

[0064] refer to Figure 2 , the energy saving information calculation method of the data center can include:

[0065] Step S202, collecting usage records of the data room, wherein the usage records include power usage information and / or temperature information of an original mode day, and daily power usage information and / or temperature information of multiple energy-saving mode days;

[0066] Step S204, generating a time series of a specified dimension from the usage record;

[0067] Step S206, using the DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix;

[0068] Step S208, determining, according to the similarity matrix, an energy-saving mode day having the highest similarity to the original mode day as the energy-saving mode comparison day;

[0069] Step S210, calculating energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day.

[0070] The disclosed embodiment collects usage records of a data room, wherein the usage records include power usage information and / or temperature information of an original mode day and power usage information and / or temperature information of each of multiple energy-saving mode days, and generates a time series of a specified dimension from the usage records, and then uses a DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix, and then determines, based on the similarity matrix, an energy-saving mode day that has the highest similarity to the original mode day as an energy-saving mode comparison day, and finally calculates energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day, thereby improving the reliability of measurement and verification of energy-saving information, improving the evaluation of energy-saving effects, and facilitating further improving the energy efficiency of the communication room.

[0071] The following is a detailed description of each step of the method for calculating energy-saving information of a data center.

[0072] In an exemplary embodiment of the present disclosure, Figure 3 As shown, the usage records of the data center include:

[0073] Step S302, collecting indoor temperature records and outdoor temperature records of the data room on a daily basis;

[0074] Step S304: determining the indoor document record and the outdoor temperature record as the temperature information.

[0075] In an exemplary embodiment of the present disclosure, Figure 4 As shown, the usage records of the data center also include:

[0076] Step S402, determining the type of power consumption record to be collected according to the type of the cabinet in the data room;

[0077] Step S404, collecting the electricity consumption records of the corresponding types of the first cabinets of each type in the data center in each specified time period on a daily basis, wherein the electricity consumption records include at least one of current, voltage value, power consumption and occupancy rate of the server;

[0078] Step S406: normalize the collected electricity usage records into the electricity usage information.

[0079] In an exemplary embodiment of the present disclosure, Figure 5 As shown, generating a time series of a specified dimension from the usage record includes:

[0080] Step S502, splicing the usage records collected in days into a feature sequence, and normalizing the data of each dimension of the feature sequence;

[0081] Step S504, averaging the normalized feature sequences of any two energy-saving mode days;

[0082] Step S506: Use the PCA algorithm to perform dimensionality reduction processing on the feature sequence after the averaging process to obtain the time series.

[0083] In an exemplary embodiment of the present disclosure, Figure 6 As shown, the DTW algorithm is used to calculate the similarity of the time series data to generate a similarity matrix including:

[0084] Step S602, using the DTW algorithm to calculate the DTW distance between the time series of the original mode day and any of the energy-saving mode days;

[0085] Step S604: Generate the similarity matrix according to the calculation result of the DTW distance.

[0086] In an exemplary embodiment of the present disclosure, the energy-saving information calculation includes energy-saving rate calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day includes:

[0087] The energy saving rate calculation formula is used to calculate the energy saving rate of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving rate calculation formula includes:

[0088]

[0089] Among them, the η s Characterize the result of energy saving rate calculation, the S rCharacterizes the power consumption of the original mode day, the S b Indicates the daily power consumption of the energy-saving mode.

[0090] In an exemplary embodiment of the present disclosure, the energy-saving information calculation includes energy-saving amount calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day further includes:

[0091] The energy saving amount calculation formula is used to calculate the energy saving amount of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving amount calculation formula includes:

[0092]

[0093] Among them, the E s Characterize the result of energy saving calculation, the E b Represents the total power consumption of the original mode day and all the energy-saving mode days.

[0094] In an exemplary embodiment of the present disclosure, a solution for calculating energy-saving information of a data center includes the following steps:

[0095] Before the start of the reporting period, weather forecast data for the reporting period shall be collected, including:

[0096] Step S802: data preprocessing and normalization.

[0097] Step S804, selecting the date with the smallest deviation from the average value as the original model day T0.

[0098] After the reporting period begins, historical data on the reporting environment and IT operations will be collected, including:

[0099] Step S806: data preprocessing and normalization.

[0100] Step S808, performing a DTW distance-based similarity calculation between the remaining energy-saving mode days within the reporting period and day T0.

[0101] Step S810: Select the date T1 with the highest similarity to the original mode day feature sequence as the energy-saving mode comparison day.

[0102] Step S812, calculating the energy saving rate based on the air conditioning power consumption at T0 and T1.

[0103] Step S814, calculating energy saving amount during the reporting period.

[0104] In an exemplary embodiment of the present disclosure, the energy-saving information calculation scheme of the data center includes the following stages:

[0105] 1. Data collection and preprocessing include the following:

[0106] Collect the outdoor temperature and humidity for 30 days of this month: After the end of the month, record the outdoor temperature T_Outdoor every hour of every day (h) and outdoor humidity H_Outdoor (h) .

[0107] Collect the current and voltage values ​​of each terminal cabinet in the computer room for 30 days of this month: After the end of the month, record the current I_N of N terminal cabinets in the computer room every day and every hour (h) , voltage value U_N (h) .

[0108] Collect the power consumption of IT equipment for 30 days this month: After the end of the month, record the power consumption W_N of N cabinets in the computer room every day and every hour (h) .

[0109] Collect the computing facility occupancy rate for 30 days this month: After the end of the month, record the occupancy rate of N servers in the computer room every hour every day CPU_N (h) or CPU_N (h) .

[0110] 2. Generate data feature sequences including the following:

[0111] 2.1 Original pattern sequence: The data of the original pattern collected in 1 on that day are spliced ​​into a feature sequence, and each dimension is normalized.

[0112] 2.2 Energy-saving mode sequence: The data of the 29 days of energy-saving mode collected in 1 are spliced ​​into feature sequences, and then 406 sequences are averaged two by two, and then 435 feature sequences are obtained.

[0113] 3. Data sequence preprocessing: Since the generated sequence has too many dimensions and is inconvenient to calculate, the PCA algorithm is used to reduce the dimension to about 20 dimensions.

[0114] 4. Similarity calculation and similar day selection: DTW algorithm is applied to align and match time series data. The similarity between different time series is measured by calculating the DTW distance, and a similarity matrix is ​​generated. The DTW similarity calculation is performed with the selected original mode day, and the sequence with the highest similarity is selected as the energy-saving mode comparison day.

[0115] In addition, to facilitate visualization, Fig. 9 Shows the outdoor temperature T_Outdoor (h) Taking a single feature as an example of similarity matching, the bold dashed line is the outdoor temperature curve 702 of the preset original pattern day, and the bold solid line is the outdoor temperature curve 704 of the most similar sequence of the original pattern day obtained through calculation.

[0116] 5. Energy saving rate calculation is to obtain the air conditioning power consumption on the energy saving day and the original mode day. The air conditioning power consumption on the energy saving day is S r If the energy-saving day sequence is obtained from the average sequence of two days, the average of the air-conditioning power consumption of the two days is taken. The air-conditioning power consumption of the original mode day is S b , the energy saving rate is η s , then the energy saving rate calculation formula is:

[0117]

[0118] 6. Energy saving calculation: Total power consumption of air conditioners during the reporting period E b , then the energy saving E s for:

[0119]

[0120] Corresponding to the above method embodiments, the present disclosure also provides an energy-saving information calculation device for a data center, which can be used to execute the above method embodiments.

[0121] Fig. 9 It is a block diagram of an energy-saving information calculation device for a data center in an exemplary embodiment of the present disclosure.

[0122] refer to Fig. 9 , the energy-saving information calculation device 900 of the data room may include:

[0123] A collection module 902 is configured to collect usage records of the data center, wherein the usage records include power usage information and / or temperature information of an original mode day, and daily power usage information and / or temperature information of multiple energy-saving mode days;

[0124] A generating module 904, configured to generate a time series of a specified dimension from the usage record;

[0125] A comparison module 906 is configured to use a DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix;

[0126] A determination module 908 is configured to determine, according to the similarity matrix, an energy-saving mode day that is most similar to an original mode day as an energy-saving mode comparison day;

[0127] The calculation module 910 is configured to calculate energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day.

[0128] In an exemplary embodiment of the present disclosure, the collection module 902 is further configured to:

[0129] Collecting indoor temperature records and outdoor temperature records of the data room on a daily basis;

[0130] The indoor document record and the outdoor temperature record are determined as the temperature information.

[0131] In an exemplary embodiment of the present disclosure, the collection module 902 is further configured to:

[0132] Determining the type of electricity consumption records to be collected according to the type of the cabinet in the data room;

[0133] Collecting the electricity consumption records of the corresponding types of the first cabinets of each type in the data center in each specified time period on a daily basis, wherein the electricity consumption records include at least one of current, voltage value, power consumption and occupancy rate of the server;

[0134] The collected electricity usage records are normalized to obtain the electricity usage information.

[0135] In an exemplary embodiment of the present disclosure, the generating module 904 is further configured to:

[0136] Splicing the usage records collected in days into a feature sequence, and normalizing the data of each dimension of the feature sequence;

[0137] Average the normalized feature sequences of any two energy-saving mode days;

[0138] The PCA algorithm is used to perform dimension reduction processing on the feature sequence after averaging processing to obtain the time series.

[0139] In an exemplary embodiment of the present disclosure, the comparison module 906 is further configured to:

[0140] Using the DTW algorithm to calculate the DTW distance between the time series of the original mode day and any of the energy-saving mode days;

[0141] The similarity matrix is ​​generated according to the calculation result of the DTW distance.

[0142] In an exemplary embodiment of the present disclosure, the calculation module 910 is further configured to:

[0143] The energy saving rate calculation formula is used to calculate the energy saving rate of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving rate calculation formula includes:

[0144]

[0145] Among them, the η s Characterize the result of energy saving rate calculation, the S r Characterizes the power consumption of the original mode day, the S b Indicates the daily power consumption of the energy-saving mode.

[0146] In an exemplary embodiment of the present disclosure, the calculation module 910 is further configured to:

[0147] The energy saving amount calculation formula is used to calculate the energy saving amount of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving amount calculation formula includes:

[0148]

[0149] Among them, the E s Characterize the result of energy saving calculation, the E b Represents the total power consumption of the original mode day and all the energy-saving mode days.

[0150] Since the functions of the device 900 have been described in detail in the corresponding method embodiments, the present disclosure will not elaborate on them here.

[0151] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0152] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0153] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0154] Refer to the following Fig.10 The electronic device 1000 according to this embodiment of the present invention will be described. Fig.10 The electronic device 1000 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0155] like Fig.10 As shown, the electronic device 1000 is in the form of a general computing device. The components of the electronic device 1000 may include but are not limited to: the at least one processing unit 1010, the at least one storage unit 1020, and a bus 1030 connecting different system components (including the storage unit 1020 and the processing unit 1010).

[0156] The storage unit stores program codes, which can be executed by the processing unit 1010, so that the processing unit 1010 performs the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification. For example, the processing unit 1010 can perform the method shown in the embodiment of the present disclosure.

[0157] The storage unit 1020 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 10201 and / or a cache storage unit 10202 , and may further include a read-only storage unit (ROM) 10203 .

[0158] The storage unit 1020 may also include a program / utility 10204 having a set (at least one) of program modules 10205, such program modules 10205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0159] Bus 1030 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0160] The electronic device 1000 may also communicate with one or more external devices 1040 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 1000, and / or communicate with any device that enables the electronic device 1000 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 1050. Furthermore, the electronic device 1000 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 1060. As shown, the network adapter 1060 communicates with other modules of the electronic device 1000 via a bus 1030. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0161] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0162] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0163] The program product for implementing the above method according to an embodiment of the present invention can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0164] Among them, the readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0165] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0166] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0167] In an exemplary embodiment of the present disclosure, a computer program product is also provided, which can be loaded or stored in any combination of one or more readable media, and can be written in any combination of one or more programming languages ​​to perform the program code of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and also conventional procedural programming languages ​​such as "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or completely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0168] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0169] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered exemplary only, and the true scope and concept of the present disclosure are indicated by the claims.

Claims

1. A method for calculating energy-saving information of a data center, characterized in that: include: Collecting usage records of the data room, the usage records including power usage information and / or temperature information of an original mode day, and daily power usage information and / or temperature information of multiple energy-saving mode days; Generate a time series of a specified dimension from the usage record; Using the DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix; Determine, according to the similarity matrix, an energy-saving mode day having the highest similarity to an original mode day as an energy-saving mode comparison day; Energy saving information is calculated based on the power consumption on the original mode day and the power consumption on the energy saving mode comparison day.

2. The method for calculating energy-saving information of a data center according to claim 1, characterized in that: The usage records of the data center include: Collecting indoor temperature records and outdoor temperature records of the data room on a daily basis; The indoor document record and the outdoor temperature record are determined as the temperature information.

3. The method for calculating energy-saving information of a data center according to claim 1, characterized in that: The use records of the data center also include: Determining the type of electricity consumption records to be collected according to the type of the cabinet in the data room; Collecting the electricity consumption records of the corresponding types of the first cabinets of each type in the data center in each specified time period on a daily basis, wherein the electricity consumption records include at least one of current, voltage value, power consumption and occupancy rate of the server; The collected electricity usage records are normalized to obtain the electricity usage information.

4. The method for calculating energy-saving information of a data center according to claim 1, characterized in that: Generating a time series of a specified dimension from the usage record includes: Splicing the usage records collected in days into a feature sequence, and normalizing the data of each dimension of the feature sequence; Average the normalized feature sequences of any two energy-saving mode days; The PCA algorithm is used to perform dimension reduction processing on the feature sequence after averaging processing to obtain the time series.

5. The method for calculating energy-saving information of a data center according to claim 1, characterized in that: The DTW algorithm is used to perform similarity calculation on the time series data to generate a similarity matrix including: Using the DTW algorithm to calculate the DTW distance between the time series of the original mode day and any of the energy-saving mode days; The similarity matrix is ​​generated according to the calculation result of the DTW distance.

6. The method for calculating energy-saving information of a data center according to any one of claims 1 to 5, characterized in that: The energy-saving information calculation includes energy-saving rate calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day includes: The energy saving rate calculation formula is used to calculate the energy saving rate of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving rate calculation formula includes: Among them, the η s Characterize the result of energy saving rate calculation, the S r Characterizes the power consumption of the original mode day, the S b Indicates the daily power consumption of the energy-saving mode.

7. The method for calculating energy-saving information of a data center according to any one of claims 1 to 5, characterized in that: The energy-saving information calculation includes energy-saving amount calculation, and the energy-saving information calculation based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day also includes: The energy saving amount calculation formula is used to calculate the energy saving amount of the power consumption of the original mode day and the power consumption of the energy saving mode comparison day, and the energy saving amount calculation formula includes: Among them, the E s Characterize the result of energy saving calculation, the E b Represents the total power consumption of the original mode day and all the energy-saving mode days.

8. An energy-saving information calculation device for a data center, characterized in that: include: A collection module configured to collect usage records of a data room, wherein the usage records include power usage information and / or temperature information of an original mode day, and daily power usage information and / or temperature information of multiple energy-saving mode days; A generating module, configured to generate a time series of a specified dimension from the usage record; A comparison module is configured to use a DTW algorithm to perform similarity calculation on the time series data to generate a similarity matrix; A determination module, configured to determine, according to the similarity matrix, an energy-saving mode day having the highest similarity to an original mode day as an energy-saving mode comparison day; The calculation module is configured to calculate energy-saving information based on the power consumption of the original mode day and the power consumption of the energy-saving mode comparison day.

9. An electronic device, characterized in that: include: Memory; as well as A processor coupled to the memory, the processor being configured to execute the method for calculating energy-saving information of a data center according to any one of claims 1 to 7 based on instructions stored in the memory.

10. A computer-readable storage medium having a program stored thereon, wherein when the program is executed by a processor, the method for calculating energy-saving information of a data center according to any one of claims 1 to 7 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for calculating energy-saving information of a data center as described in any one of claims 1 to 7 is implemented.

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